Review Article EEG Derived Neuronal Dynamics during...

Review ArticleEEG Derived Neuronal Dynamics during Meditation:Progress and Challenges

Chamandeep Kaur and Preeti Singh

Panjab University, Chandigarh 160036, India

Correspondence should be addressed to Chamandeep Kaur; [email protected]

Received 22 September 2015; Revised 11 November 2015; Accepted 15 November 2015

Academic Editor: Guido Dietrich

Copyright © 2015 C. Kaur and P. Singh.This is an open access article distributed under the Creative CommonsAttribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Meditation advances positivity but how these behavioral and psychological changes are brought can be explained by understandingneurophysiological effects of meditation. In this paper, a broad spectrum of neural mechanics under a variety of meditation styleshas been reviewed. The overall aim of this study is to review existing scientific studies and future challenges on meditation effectsbased on changing EEG brainwave patterns. Albeit the existing researches evidenced the hold for efficacy of meditation in relievinganxiety and depression and producing psychological well-being, more rigorous studies are required with better design, consideringclient variables like personality characteristics to avoid negative effects, randomized controlled trials, and large sample sizes. Abigger number of clinical trials that concentrate on the use ofmeditation are required. Also, the controversial subject of epileptiformEEG changes and other adverse effects during meditation has been raised.

1. Introduction

Meditation is a broad variety of practices. Meditationincludes relaxation supporting techniques and variousmove-ments to achieve regulation and nurturing of well-being.It is defined as the natural process of manipulating one’sstate of mind and self-regulating attention level intentionally,although it is lacking a clear operational definition [1, 2].Experienced meditators show stronger regulated features.Analysis of variousmeditation states has been done to exploredifficult neural processes. The large and complex neuronalstructures turn to more relaxed structures during meditation[3]. So meditation practitioners show distinct EEG recordingpatterns. In the beginning of each meditation style, Lutz et al.have categorized meditation as Focused Attention (FA) andopen monitoring (OM). Travis represented another categoryas automatic self-transcending according to brain patternbased EEG bands. These categories define a number ofmeditation practices [4, 5]. Minimum efforts are required toreach the state of FA and a steady focus is achieved which isevident from less activation in the amygdala [1].

Physiological and Neural Correlates of Meditation Ther-apy. Meditation practices can change the way of thinking.

Metacognitive reasoning could be made by people to predictthe discrepancy between what should be thought and whatis being thought. In [6], various neurophysiologic changeson cognition, hormonal, and autonomic systems have beentheorized while meditating. Evidences reveal the positiveeffects of meditation as it increases the level of monoamines,parasympathetic activity, and gray matter density of brainregions (reflecting emotion regulation) and reduces oxidativeeffects. These effects result in reversal of stress mediateddepression. Further research needs to be done in exploringthese changes with large samples in consideration. Thespectral power and coherence of EEG define delta, theta, andalpha frequency bands to characterize different meditationstates.

Numerous researches have been carried out to scientifi-cally explore the principle brain neurological changes duringmeditation. But neuroelectrophysiology of meditation basedstates is still an open question. A very small number of clinicalapplications of meditation have been identified and those tooare lacking in control group and concurrent antidepressantmedication group along with shorter follow-up period [6, 7].Albeit some progress has been made in theorizing the neu-rophysiological effects under meditation [4, 8–10], evoked

Hindawi Publishing CorporationAdvances in Preventive MedicineVolume 2015, Article ID 614723, 10 pageshttp://dx.doi.org/10.1155/2015/614723

2 Advances in Preventive Medicine

potential, and event related potential research in meditation[11], still rationale to quantitatively represent the neural effectsis not clear.

This review is a noteworthy contribution to review exist-ing scientific studies and future challenges on meditationeffects based on changing EEG brainwave patterns. A debateon the EEG changes duringmeditation, controversial adverseeffects of meditation, and signal processing challenges withfuture direction has been given below.

2. EEG during Meditation

A detailed quantitative analysis of neural effects under theeffect of various meditation states has been discussed below.Other studies on theEEGeffects ofmeditation could be foundin Table 1.

2.1. Buddhist Meditation. Based on open monitoring, Bud-dhist meditators are characterized by high amplitude gammaoscillations [1]. A study about the impact of Buddhist med-itation on emotional processing was presented [12]. Therewas no difference in psychological testing in experimentaland control group (CG). Also, randomized design should beincorporated in the study design.

2.1.1. Zen Meditation. Zen meditation, a type of Buddhistmeditation, is characterized by increase in slow alpha power,reflecting more internalized attention, and fast theta power,reflecting enhancedmindfulness in frontal area [9, 13]. Long-term practitioners show alpha1 rise in frontal region and betarise over occipital regions [14].

Investigations on FmTheta. During amental effort, EEG showsa decrease in alpha and this strength goes on decreasing asthe task becomes more tedious. However, frontal midlinetheta (FmTheta) increases during mental task. FmThetainvolves attention levels that appear during mental task andmeditation. It is an indicator of more demonstrative, moreactive, and less phobic activities [15]. It is defined on EEGas distinctive theta activity in frontal midline area. A studywas performed on theta signal during concentrative task(meditation) and consecutive mental task [16]. It refers toattention maintenance during mental effort. Enhanced thetaand constant occipital alpha were observed between FmThetaconditions and control. Further investigations on FmThetacan add to the underlying mechanisms of mind and body.

2.1.2. CHAN Meditation. Researchers correlated occipitalalpha wave rise during eye closed relaxation and frontal alphawave (representing mindfulness) during CHAN meditation.A method explored spatial temporal properties of differentalpha maps using microstate analysis in [17]. It reflectedmore inward attention than the CG. Another study showedthat better cortical interactions are possessed during CHANmeditation and Chakra focusing practice than the CG [18]. Inthis study, interactions among various brain networks underalpha oscillations have been explored because of Continuous

TimeWavelet Transform.This nonlinear independence anal-ysis identified the dominant alpha epochs in right and lefttemporal regions.

2.1.3. Mindfulness Meditation (MM). Meditators have re-duced physiological arousal and distraction from vaguethoughts. It can be used for treating ADHD [19]. MM caninduce neuroplasticity from earlier stages in self-referentialprocessing and increased attention to internal and exter-nal stimulus. Self-referential processing is related to DMN(Default Mode Network) [20–24].

This study theorized various state and trait effects of MMon self-referential processing. Cahn et al. have measured theeffect of Vipassana in terms of decreased delta and relativeincrease in theta over the frontal regions, though other usualchanges over alpha, beta, and theta bands have not beenobserved. The main limitation of the study was unspecificeffect of meditation practice on different frequencies, whichshould be well understood [24].

Ahani et al. [25] advanced the meditation research onMM. They supported the evidence of alpha and theta rise byobserving the spectral analysis of recorded EEG. Althoughthis randomized controlled trial was analyzed using the CG,the study was limited to novice meditators only [25]. OtherMM techniques of IBMT (Integrative Body-Mind Training)and TBRT (Triarchic Body Pathway Relaxation) have beenexplored but still very little information is available andlarge scale considerations of these techniques are required forexpert meditators [26, 27].

2.2. Transcending Meditation (TM). Various physiologicaland neural effects in long-term Jacobson’s Progressive Relax-ation (PR) meditators (a classical method of relaxation), TMmeditators, and group of beginners in PR were recorded[28]. Rare theta activity (5–7Hz) was observed in all thethree. Then, a detailed research on TM explained its effectsthat could be used for various clinical applications [29].Comparing TM-Sidhi with TM program revealed higherfrontal alpha1 and beta1 amplitudes and no change incoherence. Higher alpha1 and beta1 reflect automatic self-transcending and open monitoring, respectively. This analy-sis was conducted for frontal and parietal areas. For temporalamplitude averages, no significant changes were observed[30]. Limitation was no CG. It has also been made evidentthat TM could be used for stress reduction and improvingthe symptoms of ADHD (Attention Deficit HyperactivityDisorder) [31, 32]. In a study, individual and groupmeditationeffects were analyzed [33]. During individualmeditationwithclosed eyes, strong delta coherence and theta coherence andno alpha coherence were observed. Distinct changes in alphaand theta coherence during group meditation show morerelaxation reflected by subjects and less delta activity.

In another study, effects of TM on EEG alpha phasesynchrony have been studied [34]. An increase in synchronywas observed around frontal and occipitoparietal lobes bya time domain method. It accounts for use of this style ofmeditation for better concentrated neural processes. Eventrelated spectral perturbation (ERSP) analysis of EEG signal

Advances in Preventive Medicine 3

Table1:Meditatio

nindu

cedchangesinEE

Gbrainw

aves.

Author

Meditatio

nsty

leSubjects

Sign

alprocessin

gRe

sults

Sobo

lewskietal.[12]

Budd

hist

26—

↑ER

P1

ChangandLo

[13]

Zen

41Wavele

tAlpha

supp

ression(th

ough

morea

lpha

than

nonm

editators)

Huang

andLo

[14]

Zen

23—

↑fro

ntalalph

a2andoccipitalbeta3

Kubo

taetal.[16]

So-Soku

25Spectralanalysis

↑Fm

Theta(

reflectingcontinuo

usattention)

LoandZh

u[17]

CHAN

16Wavele

tdecom

positionandMahalanob

isfuzzyC-

means

Timep

eriodof

frontalalph

amorethanoccipitalalpha

(reflectin

gcalm

mind)

LoandCh

ang[18]

CHANandCh

akra

focusin

g20

Con

tinuo

usTimeW

avele

tTransform

Higherlateralinteractionof

dominantalpha

epochs

inrig

htandlefttempo

ralregions

(reflectin

gmore

inwardattention)

Berkovich-Ohana

etal.[23]

MM

12Spectralanalysis

(i)Statee

ffect:↑

prefrontalgamma

(ii)T

raiteffect:↓gammao

verfrontalandmidlin

eareas

Cahn

etal.[24]

MM

16ICA

(i)↓fro

ntalalph

a(ii)↑

frontalthetaa

ndgamma(

reflectingbette

rsyn

chronizedfunctio

n)

Ahani

etal.[25]

MMI

34Spectral,phase

analysis

(i)↑fro

ntaltheta(

enhancem

ento

fatte

ntionaland

workingmem

oryprocess)

(ii)M

inor↑in

right

tempo

raland

occipitalalpha

(iii)↑betaandEE

Gsynchron

y4

Xuee

tal.[26]

IBMT

45Networkanalysis

↑Fm

Theta

Chan

etal.[27]

TBRT

19FF

T(i)↑alph

aasymmetry

index(m

easure

ofpo

sitivee

motions)

(ii)↑

FmTh

eta

Warrenb

urgetal.[28]

PRandTM

6—

Rare

thetaa

ctivity

(5–7

Hz)

Travis[30]

TMandTM

-Sidhi

26Spectralanalysisandcoherencea

nalysis

DuringTM

-Sidhi

(i)↑fro

ntalalph

a1andbeta1

(ii)N

ochange

incoherence

New

ande

andRe

isman

[33]

TM(in

dividu

alandgrou

pstu

dy)

10Timefrequ

ency

analysis

Individu

alstu

dy(1)O

peneyes

(i)Strong

coherenceindelta

andtheta5

(ii)↓

alph

acoh

erence

(2)C

losedeyes

slightd

elta,almostn

otheta,andsig

nificantalpha

coherence

(3)E

xperienced

meditatorsreflectstr

ongalph

acoh

erence

andshift

tothetac

oherence

Groupmedita

tion

(1)O

peneyes

↑alph

abeing

stron

gest,

slightm

ored

eltaa

ndthetac

oherence

than

individu

alstu

dy(2)C

losedeyes6

(i)↑alph

acoh

erence

andthetac

oherence

(ii)↓

delta

activ

ityHebertetal.[34]

TM27

Timed

omainmetho

d↑alph

asyn

chrony

Eskand

ariand

Erfanian

[35]

TM10

Wavele

tdecom

position

(i)Alpha

ERSandbetaER

Sdu

ringim

aginationof

hand

movem

ent

(ii)A

lpha

ERDdu

ringrest


Table1:Con

tinued.

Author

Meditatio

nsty

leSubjects

Sign

alprocessin

gRe

sults

Kjaere

tal.[36]

Yoga

Nidra

meditatio

n8

Spectralanalysis

(i)↑thetap

ower

(ii)↓

alph

apow

er

Afta

nasa

ndGolocheikine[37]

SahajaYo

ga20

Non

linearsystem

theory:D

Cx(i)↑theta1,theta2,andalph

a1po

wers

(ii)↓

beta3(signifiesp

roblem

solvingandthinking

)

Afta

nasa

ndGolocheikine[38]

SahajaYo

ga58

FFT

(i)Lo

ng-Term

Meditators:↑

thetaa

ndalph

a1po

wer

(ii)S

hort-Term

Meditators:alpha2desynchron

ization

Baijaland

Srinivasan

[39]

SahajaSamadhi

20Spectralandcoherencea

nalysis

(i)↑fro

ntalthetad

uringdeep

meditatio

n(ii)↑

thetac

oherence

(iii)↓thetainparie

tal

Arambu

laetal.[40

]Ku

ndalini

1Spectralanalysis

↑alph

aonenterin

gmeditatio

n

Elsonetal.[44

]Anand

aMarga

11—

(i)↑theta

(ii)S

tablea

lpha-th

etab

and

Ghistae

tal.[42]

Anand

aMarga

4—

↑alph

aKhare

andNigam

[43]

Anand

aMarga

30Spectralanalysis

↑alph

aand

beta

Y.-J.

Park

andY.-B.Park[45]

PB58

FFT

(i)↑alph

a1(ii)↓

theta

Tsaietal.[46

]Ad

vanced

breathing

1Sing

letim

eseriesa

nalysis

↑bilateralalpha

andtheta

Lehm

annetal.[47]

TibetanBu

ddhists

,QiGon

g,Sahaja

Yoga,A

nand

aMarga,and

Zen

13 15 14 14 15

Lagged

intracortic

alcoherence

Lowered

interdependenceb

etweendifferent

functio

nsas

show

nby

delta

andbeta2band

activ

ities

Barnho

fere

tal.[49]

Mindfulnessbreathingandloving

kind

ness

8 7FF

TStrong

leftprefrontalactiv

ation(reflectsstr

ongtend

ency

form

otivationandpo

sitivity

)

Vialatteetal.[58]

BhramariP

ranayama

8Com

plex

Morletw

aveletsa

ndFo

urier

analysis

↑fre

quencies

inbeta(15–35)a

ndgamma(>35)a

ndincreasedthetaa

ctivity

1:stabilitytowards

negativ

estim

uli,2:moreinternalized

attention,

3:op

enmon

itorin

g,4:im

proved

functio

nalintegratio

n,5:du

etoaw

ake,alert,andop

eneyes,and

6:relaxedanddeeper

levelofm

editatio

n.


during TM practice has been presented for analyzing mindcontrollability of brain-computer interaction systems [35].No CG was used for analysis.

2.3. Yoga Meditation. Evidences showed heightened thetaEEG activity during Yoga Nidra and Sahaja Yoga but morecontrol group designed study is needed [36, 37]. DuringSahaja Yoga, LTM (Long-Term Meditators) showed highertheta and alpha1 power and STM (Short-Term Meditators)showed alpha2 desynchronization [38]. EEG mechanismsduring Sahaja Samadhi (concentrative) meditation reflectincrease in theta power and theta coherence in frontal areaduring deep meditation [39]. Again comparison with CG isrequired.

EEG pattern of a Kundalini Yoga master and AnandaMarga have been theorized as reflectingmore alpha and thetaband [40–44]. Still very few studies have been conducted forYoga meditation considering the proficiency levels.

2.4. OtherMeditation Practices. Paced Breathing (PB), whichis a type of Su-Soku meditation, is a method of voluntarybreathing [45]. It causes change in EEG parameters (increasein low frequency and high frequency alpha power anddecrease in theta power). PB is advantageous compared toother meditative states [45].

An oscillatory mechanism of EEG during advancedbreathingmeditation, a new area to explore, has been studiedin [46]. This finding supported the fact that the internal-ized attention is continuously enhanced and is noteworthyas reported by rise in theta activities, while relaxation isprominent only after deep phase of meditation as reportedby changes in alpha activities [46].

2.5. Other Combined Studies. It has been revealed in a studythat electric function connectivity differs in five traditions ofmeditation [47]. These are Tibetan Buddhists (TB), Qigong,Sahaja Yoga (SY), Ananda Marga Yoga (AY), and Zen [47].The results have been taken for delta and beta2 bands becauseall five meditations showed significant changes in these twobands. In delta band of TB group, moving out of meditationshowed left to right posterior connection while it showedanterior left to right posterior connectivity in AY group[47]. Such types of guesses evidently become impossible,for example, Qigong, since it includes a large number ofconnections.This research shows the common features in fivetraditions ofmeditation but with noCG and it did not explorethe difference. Analysis of principal functional connectivitiesduring delta band reflected that interdependence betweendifferent functions is lowered with practicing meditationirrespective of meditation style and inhibitory and excitatory(delta and beta2 band activities) brain region connectivitiesshow this reduction [47, 48].

In another study, state effects of two meditation styles,mindfulness breathing and loving kindness (or metta) medi-tation, have been investigated [49]. Effects on prefrontal alphaasymmetry have been discussed. Subjects low in broodingshowed response to loving kindness meditation while theopposite was observed for subjects with high brooding.

Comparisons to rest group showed useful state effects of boththe styles of meditation. It accounts for their clinical use forpreviously depressed patients, although various limitationslike unspecific factors, small sample size, and novice subjectswere observed in the study [49].

3. Controversial Studies

It has also been reported thatmeditation has an adverse effectof predisposing to epileptogenesis panic attacks, overex-cited central nervous system, paradoxical rise in anxiety,becoming more hypercritical, disorientation, and high BP[10]. Regarding the use of meditation for high BP, morerandomized clinical trials are required that could providecertain results [50]. Some positive effects might becomenegative if overexpressed in those with individual consti-tutional neurophysiological properties [EEG guided med.].Deep meditation gives rise to high frequency gamma bandbursts [51].The patients with general epilepsy show increasedgamma band activity especially 30–50Hz in resting interictalEEG [52, 53]. Epileptiform EEG changes have been theorizedin TMmeditators. So some studies accounted for meditationresulting in epilepsy but some have rejected such claims [51–57]. Meditation predisposing to epilepsy is a controversialsubject that requires scientific study.

During Bhramari Pranayama (BhPr), paroxysmal gamma(PGW) has been observed [58]. Using complex Morletwavelets and Fourier analysis, features were extracted as highfrequencies in beta (15–35) and gamma (>35) and increasedtheta activity. BhPr can represent epileptic activity sincehigher frequency epilepsy also exhibits such spiky shape andactivity in temporal lobe as seen in BhPr [58]. Another studyhas brought light to TM as aggravating or treating epilepsy[59].

4. Signal Processing Challenges

Signal processing can add to this field of study [60]. Thescalp electrodes, which contain the brain activity in termsof electric potentials, give signals which can be processedusing SP algorithms to measure different mental activitiesand to reveal cognitive tasks. The internal language of themind can be understood using different EEG patterns fromelectromagnetic field activity [61, 62]. EEG includes signalsthat are associated with awareness, encouragement, andcognitive load and affecting state of load [63–65].

EEG data is characterized by delta, theta, alpha, beta, andgamma [66]. A detailed description of assigned EEG bandshas been given in Table 2.

A pronounced attempt to characterize EEG signaturesfor different types of meditation has been contributed byTravis and Shear [4]. They have not allocated rating but havevalued the nature of meditation styles. A superior research inmeditation is still required to categorize the EEG signaturescorresponding to different meditation practices [4, 5].

Directly observing the nonlinear and nonstationary EEGraw data in time domain is a very tedious task [67]. Sovarious linear andnonlinear signal processing techniques and


Table2:EE

Gbrainw

avefrequ

ency

band

s[4,70,78–81].

Frequencyband

swith

subb

ands∗

Brainregion

sCh

aracteris

tics

Pathologies

Delta(<4H

z)(i)

Fron

talinadults

(ii)P

osterio

rinchild

ren

(i)Tend

ency

tobe

oftheh

ighestam

plitu

de(ii)D

uringdeep

sleep

stagesinadults,

appear

ininfantsu

pto

oney

ear

(iii)Slow

estb

rain

rhythm

s(iv

)Minim

alconsciou

sbrain

involved

(v)F

IRDA(FrontalInterm

ittentR

hythmicDelta):2

to3H

zhaving

amplitu

de50–100

mVgeneratedfro

ntally,

inwake

adultsneedingdifferentiatio

nfro

martifactslik

esloweye

blinks

(vi)OIRDA(O

ccipita

lIntermittentR

hythmicDelta):linked

largely

with

seizures

inchild

ren

(1)F

ocaldelta

activ

ity:abn

ormalindicatin

glesio

ns(2)L

ower

delta

power:com

plex

depressio

n,continual

migraine,clo

sedpo

sterio

rhead/neck

damage

(3)E

xcessd

eltaa

ctivity∗∗:learningdisability,Alzh

eimer’s

disease,edem

a

Theta(

4–8H

z)(i)

Theta1

(4–6

Hz)

(ii)Th

eta2

(6–8

Hz)

Medialprefro

ntalandanterio

rcingu

late

cortex

(i)Amplitu

de30–6

0𝜇V(FmTh

eta)

(ii)Inno

rmalchild

renandinfants,in

adultsdu

ring

drow

siness,sle

ep,and

meditatio

nrelaxedsta

te(iii)Neuralind

icator

ofinnerp

rocesses

requ

iring

self-managem

ent

(iv)F

mTh

eta:thetar

hythm

of6-7H

zcenteredarou

nd6.5H

z,ag

oodindicatoro

fcon

tinuo

usattention,

linkedwith

less

anxiety,lessph

obicactiv

ity

Inno

rmalaw

aken

adults,

very

smallthetaactiv

itybu

tahigh

valuea

ccou

ntsfor

pathologicalcond

ition

s

Alpha

(8–13H

z)(i)

Alpha1(8–8.9H

z)(ii)A

lpha2(9–10.9H

z)(iii)Alpha3(11–12.9Hz)

(i)Po

sterio

roneach

sideo

fthe

head

with

high

eram

plitu

deon

leadingsid

e(ii)F

astera

tposterio

r,slo

wer

atanterio

rrecordingpo

sitions

(i)Amplitu

de<50𝜇V

(ii)D

ominantfrequ

ency

inadults

(iii)Tasksrequirin

gattention,

semantic

mem

ory

(iv)E

asily

seen

with

closed

eyes

andun

derm

entalinactive

cond

ition

s(v)L

ower

alph

aband(alpha1,alph

a2)isa

nindexof

internalized

attention

(vi)Highalph

aband(alpha3)

isan

indexof

engagementin

task

demands

(vii)

ERD:duringbigger

task

demands,alpha

isdesynchron

ized

andthetaissyn

chronized

(viii)A

lpha

blocking

occurswheneyes

areo

penedin

awelllit

room

.Thew

aves

ared

ominated

byfastlowam

plitu

debeta

rhythm

s(ix

)Murhythm

:alpha

activ

ityin

sensorim

otor

cortex

Alpha

coma,ad

iffused

alph

ainEE

Goccursin

comaw

hich

does

notrespo

ndto

externalstimuli

Beta(13–30

Hz)

(i)Be

ta1(13–18H

z)(ii)B

eta2

(18–22

Hz)

(iii)Be

ta3(22–30

Hz)

(i)Fron

tocentral

(ii)P

osterio

r-occipitalininfantsw

hich

shiftstofro

ntalareasa

sweg

rowup

(i)Usuallyam

plitu

de≤30𝜇V

(ii)Inallage

grou

psin

alertand

anxiou

ssub

jectse

nhancedby

expectationsta

tes

(iii)Be

ta1con

sistsof

corticothalamicfeedback

loop

that

changesa

ttentionlevel,betabu

rstsshift

thes

ystem

into

attentionsta

tethatallowgammas

ynchronizatio

n(iv

)Beta2

durin

gfocusedmanagerialprocessing

(1)D

ecreased

betaactiv

ity:focallesio

ns,stro

ke,ortum

ordiffu

sedenceph

alop

athy

such

asanoxia

(2)E

xcessb

etaa

ctivity

durin

galcoho

lism

alon

gwith

decreasedalph

aand

theta

Gam

ma(>30

Hz)

Differentb

rain

region

s

(i)Ex

tremely

fastfre

quency

with

lowestamplitu

de(ii)P

rovidessyn

aptic

plasticity

forlon

g-term

mem

oryby

closelytracking

thelocalchange

inbloo

dflo

w(iii)Higherinfocusedstimuli

Sometim

esof

noclinicalinterestand

filteredou

tinEE

Grecordings

∗Alth

ough

mostresearchersusethese

universally

accepted

frequ

ency

ranges,since

frequ

ency

varie

swith

age,neurologicaldiseases,brain

volume,task

requ

irements,

andmem

oryperfo

rmance,som

eresearchers

usetheirow

nrangeo

fbou

ndaries.

Also

,insomes

tudies,decim

alvalues

have

been

used

ford

efining

frequ

ency

band

sinstead

ofwho

lenu

mbers.

∗∗Increaseddelta

activ

ityconsidered

with

norm

aladultsperfo

rmingcalculations,reactiontim

etestsin

somes

tudies.


their correlation to physiology have been proposed. Featureextraction algorithms acquire the spectral information fromthe preprocessed raw signal.

Time frequency analysis is beneficial in clarifying rhyth-mic information in EEG signals. Coherence techniques canalso be used. Spectral covariance or coherence involvesmeasurement of phase regularity between signal pairs in eachfrequency band.Higher alpha-theta coherence has been iden-tified as meditation capability trait which appears intra- andinterhemispherical in meditation [68]. As coherence cannotseparate amplitude information and phase information whilerelating two signals, it measures roundabout phase lockingonly. Synchrony technique is being used rather than havingspectral or coherence analysis. It is quantification of degreeof phase locking between different narrowband signals [69].

Linear methods used are ICA (Independent ComponentAnalysis), CSP (Common Spatial Patterns), LD (Linear Dis-criminator), and linear prediction method [70]. In otherwords, a wide range of algorithms extract the information inEEG signals like algorithms based on Fast Fourier Transform,Hilbert-Huang Transform, Wavelet Transform, rule basedexpert systems, and numerous other algorithms to define thetemporal extents [70–72]. A method based on PBFT (PeriodBased Frequency Tracker) has been proposed to keep track ofrhythmic variations of alpha frequencies [73]. Though STFT(Short Time Fourier Transform) can analyze such spectralvariations, this method proved better in terms of fairerfrequency resolution [73]. Also, problem of asymmetricalperiodicity of EEG has been solved reliably and efficiently.

The inherent inhomogeneous characteristics and multi-nature are dealt with using nonlinear signal processing tech-niques on the basis of various parameters, for example, CD(CorrelationDimension), LLE (Largest Lyapunov Exponent),and H (Hurst exponent) [70]. Four-channel analysis of EEGhas been given for Compressed Spectral Array (CSA), therunning fractal dimension, and running attractor dimension[74]. CSA yields interesting features. The running attractor ismore efficient in analyzing neural dynamics. Multiscale frac-tal dimension (MSFD) technique is another area of researchto explain the multiscale temporal patterns of EEG [75].Nonlinear methods are better than time domain, frequencydomain, and linear methods.

5. Future Work and Challenges

A crisp and consistent observation of a particular EEGcomponent and its changing direction as either increasing ordecreasing for different meditation practices is still required.Numerous researches have been carried out to scientificallyexplore the underlying brain neuroelectrical effects duringmeditation but still neurophysiological effect of meditation isan open question.Though it has been theorized that a typicalEEG signature of meditation can be increase in theta, alphaband power, decrease in at least alpha frequency, and spreadof alpha coherence across cortex, its realization needs furtherresearch [4]. Also finding a comparable nonmeditating groupas a control group is very difficult [11]. The main limitation isabsence of control group.Whether the changes in EEG signals

classify the restrained states of consciousness is questionable,although a pronounced clarification has been contributedby Travis and Shear. Further investigations are required toquantitatively represent the activities during FmTheta andactivities concerning DMN during different styles of medi-tation. For EEG during DMN, the proposed approaches canbe cross power spectra techniques, partial coherence functioncomputation techniques, and operational architectonics tech-niques. Further studies have been suggested to consider extrafrequency ranges and cross-correlation between EEG signals[75]. Very few conclusions have been derived regarding theexpertise level of Yoga meditation. Neurobiological studyof various types of Buddhist, Yoga, and other meditationsstyles is still to be explored. Also, meditation predisposingto epileptic seizure as well as some other negative effects isa controversial subject that requires technical discussion.

Signal processing can add to this field of study. EEG is thebest diagnostic tool to provide firm information about brainactivities and temporal dynamics related to these activitieswithin millisecond range but if analyzing technique is poorit could result in misinterpretation and may ignore certainneural correlates [67]. So it can be said that EEG is misjudgedhighly.More processing tools and engineering approaches arerequired to be investigated for exploring EEG information[76].

Also meditation effects on the brain activity measured byEEG could be contaminated by the electromuscular artifacts.EEG rhythms show 6 times less power in 25–30Hz band and100 times less 40–100Hz power in paralyzed subjects [77].So muscle contamination is an important issue in defininggamma EEG during meditation.

6. Conclusion

Nowadays, complementary therapies like meditation arestarting to be used in clinical practices. Understandingneuroelectrical effects of meditation is an important area ofresearch, especially considering the application of meditationtechniques in clinical practice and therapy. Studies basedon EEG brainwave signals can help medical practitioners tocheck the activity level of brain and based on the healthstate, differentmeditation practices can be applied to progressmental fitness. In this paper, a broad spectrum of neuralmechanics under a variety of meditation styles has beenreviewed. A detailed quantitative analysis of various med-itation states like Zen, CHAN, mindfulness, TM, Vipas-sana, Kundalini, Yoga, and other meditation styles has beendescribed by means of EEG bands and coherence. It hasbeen concluded that increased independent brain processesare observed compared to task-free resting during medita-tion. More rigorous studies are required with better design,considering client variables like personality characteristics toavoid risks, randomized controlled trials, long-term effects,and large sample sizes. More rigorous clinical trials thatconcentrate on the use of meditation are also required.Investigations on further activities can add neuroanatomy toexplore the mechanisms of mind and body. Signal processingaspects in the field of cognitive neuroplasticity have also been


discussed. A superior research is still required to categorizethe EEG signatures corresponding to different practices.

In summary, highly developed approaches to the researchof meditation will scientifically explore the underlying brainfunctions which may be beneficial for social well-being. Alarge scale research has been done to explore the neurophys-iologic effects of meditation but still much is to be done toexplore this area as suggested by various studies.

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this review paper.

Acknowledgment

The authors would like to thank their faculty members whohave given them great suggestions and support.

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